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Search Results: 1 - 10 of 31033 matches for " Thomas Rusch "
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IRT models with relaxed assumptions in eRm: A manual-like instruction
REINHOLD HATZINGER,THOMAS RUSCH
Psychology Science Quarterly , 2009,
Abstract: Linear logistic models with relaxed assumptions (LLRA) as introduced by Fischer (1974) are a flexible tool for the measurement of change for dichotomous or polytomous responses. As opposed to the Rasch model, assumptions on dimensionality of items, their mutual dependencies and the distribution of the latent trait in the population of subjects are relaxed. Conditional maximum likelihood estimation allows for inference about treatment, covariate or trend effect parameters without taking the subjects' latent trait values into account. In this paper we will show how LLRAs based on the LLTM, LRSM and LPCM can be used to answer various questions about the measurement of change and how they can be fitted in R using the eRm package. A number of small didactic examples is provided that can easily be used as templates for real data sets. All datafiles used in this paper are available from http://eRm.R-Forge.R-project.org/
Community Structure and Functional Gene Profile of Bacteria on Healthy and Diseased Thalli of the Red Seaweed Delisea pulchra
Neil Fernandes, Peter Steinberg, Doug Rusch, Staffan Kjelleberg, Torsten Thomas
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0050854
Abstract: Disease is increasingly viewed as a major factor in the ecology of marine communities and its impact appears to be increasing with environmental change, such as global warming. The temperate macroalga Delisea pulchra bleaches in Southeast Australia during warm summer periods, a phenomenon which previous studies have indicated is caused by a temperature induced bacterial disease. In order to better understand the ecology of this disease, the bacterial communities associated with threes type of samples was investigated using 16S rRNA gene and environmental shotgun sequencing: 1) unbleached (healthy) D. pulchra 2) bleached parts of D. pulchra and 3) apparently healthy tissue adjacent to bleached regions. Phylogenetic differences between healthy and bleached communities mainly reflected relative changes in the taxa Colwelliaceae, Rhodobacteraceae, Thalassomonas and Parvularcula. Comparative metagenomics showed clear difference in the communities of healthy and diseased D. pulchra as reflected by changes in functions associated with transcriptional regulation, cation/multidrug efflux and non-ribosomal peptide synthesis. Importantly, the phylogenetic and functional composition of apparently healthy tissue adjacent to bleached sections of the thalli indicated that changes in the microbial communities already occur in the absence of visible tissue damage. This shift in unbleached sections might be due to the decrease in furanones, algal metabolites which are antagonists of bacterial quorum sensing. This study reveals the complex shift in the community composition associated with bleaching of Delisea pulchra and together with previous studies is consistent with a model in which elevated temperatures reduce levels of chemical defenses in stressed thalli, leading to colonization or proliferation by opportunistic pathogens or scavengers.
Influencing elections with statistics: Targeting voters with logistic regression trees
Thomas Rusch,Ilro Lee,Kurt Hornik,Wolfgang Jank,Achim Zeileis
Statistics , 2013, DOI: 10.1214/13-AOAS648
Abstract: In political campaigning substantial resources are spent on voter mobilization, that is, on identifying and influencing as many people as possible to vote. Campaigns use statistical tools for deciding whom to target ("microtargeting"). In this paper we describe a nonpartisan campaign that aims at increasing overall turnout using the example of the 2004 US presidential election. Based on a real data set of 19,634 eligible voters from Ohio, we introduce a modern statistical framework well suited for carrying out the main tasks of voter targeting in a single sweep: predicting an individual's turnout (or support) likelihood for a particular cause, party or candidate as well as data-driven voter segmentation. Our framework, which we refer to as LORET (for LOgistic REgression Trees), contains standard methods such as logistic regression and classification trees as special cases and allows for a synthesis of both techniques. For our case study, we explore various LORET models with different regressors in the logistic model components and different partitioning variables in the tree components; we analyze them in terms of their predictive accuracy and compare the effect of using the full set of available variables against using only a limited amount of information. We find that augmenting a standard set of variables (such as age and voting history) with additional predictor variables (such as the household composition in terms of party affiliation) clearly improves predictive accuracy. We also find that LORET models based on tree induction beat the unpartitioned models. Furthermore, we illustrate how voter segmentation arises from our framework and discuss the resulting profiles from a targeting point of view.
Model trees with topic model preprocessing: An approach for data journalism illustrated with the WikiLeaks Afghanistan war logs
Thomas Rusch,Paul Hofmarcher,Reinhold Hatzinger,Kurt Hornik
Statistics , 2013, DOI: 10.1214/12-AOAS618
Abstract: The WikiLeaks Afghanistan war logs contain nearly $77,000$ reports of incidents in the US-led Afghanistan war, covering the period from January 2004 to December 2009. The recent growth of data on complex social systems and the potential to derive stories from them has shifted the focus of journalistic and scientific attention increasingly toward data-driven journalism and computational social science. In this paper we advocate the usage of modern statistical methods for problems of data journalism and beyond, which may help journalistic and scientific work and lead to additional insight. Using the WikiLeaks Afghanistan war logs for illustration, we present an approach that builds intelligible statistical models for interpretable segments in the data, in this case to explore the fatality rates associated with different circumstances in the Afghanistan war. Our approach combines preprocessing by Latent Dirichlet Allocation (LDA) with model trees. LDA is used to process the natural language information contained in each report summary by estimating latent topics and assigning each report to one of them. Together with other variables these topic assignments serve as splitting variables for finding segments in the data to which local statistical models for the reported number of fatalities are fitted. Segmentation and fitting is carried out with recursive partitioning of negative binomial distributions. We identify segments with different fatality rates that correspond to a small number of topics and other variables as well as their interactions. Furthermore, we carve out the similarities between segments and connect them to stories that have been covered in the media. This gives an unprecedented description of the war in Afghanistan and serves as an example of how data journalism, computational social science and other areas with interest in database data can benefit from modern statistical techniques.
Molecular Tools for the Detection of Nitrogen Cycling Archaea
Antje Rusch
Archaea , 2013, DOI: 10.1155/2013/676450
Abstract:
Molecular Tools for the Detection of Nitrogen Cycling Archaea
Antje Rusch
Archaea , 2013, DOI: 10.1155/2013/676450
Abstract: Archaea are widespread in extreme and temperate environments, and cultured representatives cover a broad spectrum of metabolic capacities, which sets them up for potentially major roles in the biogeochemistry of their ecosystems. The detection, characterization, and quantification of archaeal functions in mixed communities require Archaea-specific primers or probes for the corresponding metabolic genes. Five pairs of degenerate primers were designed to target archaeal genes encoding key enzymes of nitrogen cycling: nitrite reductases NirA and NirB, nitrous oxide reductase (NosZ), nitrogenase reductase (NifH), and nitrate reductases NapA/NarG. Sensitivity towards their archaeal target gene, phylogenetic specificity, and gene specificity were evaluated in silico and in vitro. Owing to their moderate sensitivity/coverage, the novel nirB-targeted primers are suitable for pure culture studies only. The nirA-targeted primers showed sufficient sensitivity and phylogenetic specificity, but poor gene specificity. The primers designed for amplification of archaeal nosZ performed well in all 3 criteria; their discrimination against bacterial homologs appears to be weakened when Archaea are strongly outnumbered by bacteria in a mixed community. The novel nifH-targeted primers showed high sensitivity and gene specificity, but failed to discriminate against bacterial homologs. Despite limitations, 4 of the new primer pairs are suitable tools in several molecular methods applied in archaeal ecology. 1. Introduction Archaea have been detected in virtually all types of extreme and moderate environments. They play multiple ecological roles, colonizing certain newly emerging habitats [1, 2], interacting with animals such as corals [3, 4], sponges [5, 6], termites [7], or ruminants, forming part of microbe-microbe symbioses [8–10], and driving numerous processes in the biogeochemical C, N, S, and Fe cycles. In addition to relatively well-studied isolates of extremophilic or methanogenic Archaea, uncultured representatives have been detected by their 16S rRNA genes or by metabolic genes that classify their owners into the guilds of sulfate reducers, diazotrophs, ammonia oxidizers, or methanogens. Despite their widespread occurrence, a mere handful of nonmethanogenic Archaea has been isolated from moderate habitats [11–13]. While such isolates are indispensable for insight into archaeal ecophysiology, they have been recalcitrant to cultivation efforts, so that our current ecological research on mesophilic Archaea largely depends on cultivation-independent methods. Molecular
The Association between Active and Passive Smoking and Latent Tuberculosis Infection in Adults and Children in the United States: Results from NHANES
Ryan P. Lindsay, Sanghyuk S. Shin, Richard S. Garfein, Melanie L. A. Rusch, Thomas E. Novotny
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0093137
Abstract: Background Few studies assessing the relationship between active and passive smoking and tuberculosis have used biomarkers to measure smoke exposure. We sought to determine the association between active and passive smoking and LTBI in a representative sample of US adults and children. Methods We used the 1999–2000 US National Health and Nutrition Examination Survey (NHANES) dataset with tuberculin skin test (TST) data to assess the association between cotinine-confirmed smoke exposure and latent tuberculosis infection (LTBI) among adults ages ≥20 years (n = 3598) and children 3–19 years (n = 2943) and estimate the prevalence of smoke exposure among those with LTBI. Weighted multivariate logistic regression was used to measure the associations between active and passive smoking and LTBI. Results LTBI prevalence in 1999–2000 among cotinine-confirmed active, passive, and non-smoking adults and children was 6.0%, 5.2%, 3.3% and 0.3%, 1.0%, 1.5%, respectively. This corresponds to approximately 3,556,000 active and 3,379,000 passive smoking adults with LTBI in the US civilian non-institutionalized population in 1999–2000. Controlling for age, gender, socioeconomic status, race, birthplace (US vs. foreign-born), household size, and having ever lived with someone with TB, adult active smokers were significantly more likely to have LTBI than non-smoking adults (AOR = 2.31 95% CI 1.17–4.55). Adult passive smokers also had a greater odds of LTBI compared with non-smokers, but this association did not achieve statistical significance (AOR = 2.00 95% CI 0.87–4.60). Neither active or passive smoking was associated with LTBI among children. Among only the foreign-born adults, both active (AOR = 2.56 (95% CI 1.20–5.45) and passive smoking (AOR = 2.27 95% CI 1.09–4.72) were significantly associated with LTBI. Conclusions Active adult smokers and both foreign-born active and passive smokers in the United States are at elevated risk for LTBI. Targeted smoking prevention and cessation programs should be included in comprehensive national and international TB control efforts.
“Elude” – the making of an impossible game
Doris C. Rusch
E-Beratungsjournal , 2011,
Abstract: Right after the Games for Health Conference in 2009, Doris C. Rusch and Attila Ceranoglu decided to work on a game about depression: A game that actually intends to make the feelings of depression itself experientially tangible to players. They decided to use the internet and virtual reality to reach the digital natives easily, and to raise awareness of the difficulties and problems of depression amongst young people (and therefore become more willing to either seek help for themselves or others). But how to create such a game about depression? How to create a game that would be no fun? Rusch and Ceranoglu found the answers and now Elude“ is done!
Social and Structural Factors Associated with HIV Infection among Female Sex Workers Who Inject Drugs in the Mexico-US Border Region
Steffanie A. Strathdee,Remedios Lozada,Gustavo Martinez,Alicia Vera,Melanie Rusch,Lucie Nguyen,Robin A. Pollini,Felipe Uribe-Salas,Leo Beletsky,Thomas L. Patterson
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0019048
Abstract: FSWs who inject drugs (FSW-IDUs) can acquire HIV through high risk sexual and injection behaviors. We studied correlates of HIV infection among FSW-IDUs in northern Mexico, where sex work is quasi-legal and syringes can be legally obtained without a prescription.
Throwing the dice for the diagnosis of vaginal complaints?
Andreas Schwiertz, David Taras, Kerstin Rusch, Volker Rusch
Annals of Clinical Microbiology and Antimicrobials , 2006, DOI: 10.1186/1476-0711-5-4
Abstract: We evaluated the misjudgement rate of the aetiology of vaginal complaints. A total of 220 vaginal samples from women with a vaginal complaint were obtained and analysed for numbers of total lactobacilli, H2O2-producing lactobacilli, total aerobic cell counts and total anaerobic cell counts including bifidobacteria, Bacteroides spp., Prevotella spp. Additionally, the presence of Atopobium vaginae, Gardnerella vaginalis, Candida spp. and Trichomonas vaginalis was evaluated by DNA-hybridisation using the PCR and Affirm VPIII Microbial Identification Test, respectively.The participating physicians diagnosed Bacterial vaginosis (BV) as origin of discomfort in 80 cases, candidiasis in 109 cases and mixed infections in 8 cases. However, a present BV, defined as lack of H2O2-lactobacilli, presence of marker organisms, such as G. vaginalis, Bacteroides spp. or Atopobium vaginae, and an elevated pH were identified in only 45 cases of the women examined. Candida spp. were detected in 46 cases. Interestingly, an elevated pH corresponded solely to the presence of Atopobium vaginae, which was detected in 11 cases.Errors in the diagnosis of BV and candida vulvovaginitis (CV) were high. Interestingly, the cases of misjudgement of CV (77%) were more numerous than that of BV (61%). The use of Amsel criteria or microscopy did not reduce the number of misinterpretations. The study reveals that the misdiagnosis of vaginal complaints is rather high.The microbiology of the vagina is complex, containing 109 bacterial colony forming units per gram of secretions and potentially dozens of species. It is mainly dominated by members of the genus Lactobacillus, which are capable of H2O2-production and lactic acid, thereby maintaining the generally acidic vaginal pH. Age, phase of the menstrual cycle, sexual activity, contraceptive choice, pregnancy, presence of necrotic tissue or foreign bodies, and use of hygienic products or antibiotics can disrupt this ecosystem. A disturbed vaginal microbiot
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